Quant 1

Question 1

Individuals vs. Variables

Answer 1

Individuals - the things we count or measure
Variables - Some characteristics of the individuals

Students - years in school, GPA
Cars - Color, mfg., price

Question 2

Types of data

Answer 2

Categorical - Verbal (explaination) or coded (type 1, 2, 3 …)
Numerical - Discrete (whole nums) or continuous (fractional or rounded to a whole num)

Question 3

Categorical Data

Answer 3

Puts individuals into groups
-year in school
-color
-type of climate

Question 4

Numerical Data

Answer 4

Assigns numbers
-GPA
-Price
-Number of errors

Question 5

Discrete vs Continuous

Answer 5

Discrete is countable, observable, integer value, or counted on hand.
Continuous is fraction or decimal, measured by an instrument, possibly turned discrete by rounding.

Question 6

Descriptive, Predictive and Prescriptive Analytics

Answer 6

What happened? What will happen? What should we do going forward?

Question 7

CRM

Answer 7

Customer Relationship Management

Question 8

Post hoc fallacy

Answer 8

If A precedes B, then A causes B. Assuming causality.

Question 9

Observation

Answer 9

A single member of a collection

Question 10

Data Set

Answer 10

All the values of all of the variables of all of the observations

Question 11

Coding categorical info

Answer 11

Assign a numerical value to a nonnumerical variable.

Question 12

Time series data

Answer 12

x axis is equally spaced time gaps

Question 13

Nominal Data

Answer 13

Categorical data. Qualitative, categorical, or classification. Weakest level of measurement

Question 14

Ordinal Data

Answer 14

Implies ranking. (size of vehicle: Full-sized (1), compact (2), subcompact (3)) Stronger than nominal data but still weak. No averages can be computed because there is no definition of the distance between each variable.

Question 15

Interval Data

Answer 15

eg. Survey data on satisfaction. Can compute things like average. No meaningful zero point.

Question 16

Ratio Data

Answer 16

Meaningful zero point. All mathematical operations are applicable including logs and ratios. Zero does not have to be observable in the data (ie baby weights). Ratio data can be recoded down to ordinal data but the inverse is not possible. (ie categorizing blood pressures into ‘normal’, ‘elevated’ or ‘high’

Question 17

Likert Scale

Answer 17

Survey research scale indicative of Interval Data. Strongly agree to strongly disagree. Distance between coded responses can be seen as equal, although ratios are not applicable. 4 is not twice 2.

Question 18

Population

Answer 18

All of the items we are interested in. For example: all of the passengers on a plane (finite) or all of the coke products produced in an ongoing line (~infinite)

Question 19

Sample

Answer 19

A subset of the population that we will actually analyze

Question 20

Census

Answer 20

While a sample involves looking at a subset, a census looks at all of the individuals. The accuracy may be illusory

Question 21

When a sample may be better than a census

Answer 21

Infinite Population - indefinite pop
Destructive testing - testing destroys population
Timely results - faster
Accuracy - too resource intensive to do a census
Cost - too expensive to do a census
Sensitive info

Question 22

When a census may be preferable to a sample

Answer 22

Small population
Large sample size
Database exists
Legal requirements

Question 23

Parameter

Answer 23

A measurement or characteristic of the population (mean or proportion) Usually represented by mu and pi

Question 24

Statistic

Answer 24

A numerical value calculated from a sample (mean or proportion). Usually represented by x bar and p.